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Lead Data Architect / Technical Delivery Lead –

- Data Retention Platform?
- Bengaluru | Full-Time, In OfficeWe are looking for a senior, hands-on Data Architect and Technical Delivery Lead to lead the design and engineering delivery of a large-scale data and document retention platform within a highly regulated financial-services environment.

This is not a traditional Project Manager role.

We need someone who can design the architecture, understand the code and data, challenge technical decisions, and lead engineering discussions, while also taking ownership of delivery across multiple teams.The successful candidate must be equally comfortable at a whiteboard designing the architecture, reviewing a PySpark/SQL implementation with engineers, troubleshooting a data pipeline, and communicating delivery status and technical decisions to senior stakeholders.

The ProjectThe platform will ingest, process, retain and retrieve large volumes of data and documents required to satisfy regulatory retention requirements, privacy policies, litigation and legal holds.It must support reliable retrieval for regulatory inquiries, audits, litigation requests and other business requirements.

What You Will OwnYou will provide the technical and delivery leadership for the platform, including:Own and evolve the end-to-end data architecture across ingestion, transformation, storage, retention, archival and retrieval.Translate business and regulatory retention requirements into technical architecture, data models and engineering requirements.Lead engineering discussions and make/challenge decisions around data pipelines, data models, storage, performance, scalability, lineage and controls.Work hands-on with Databricks, PySpark, SQL, Airflow and AWS data services.Design and review batch/data pipelines from source systems through processing and into retention/archive layers.Define appropriate use of PySpark/Spark for large-scale processing and SQL for transformation, reconciliation, controls and retrieval.Design orchestration patterns using Airflow, including dependencies, scheduling, retries,



monitoring and failure handling.Define data models and metadata structures supporting retention periods, regulatory basis, source lineage, legal holds and retrieval.Review engineering designs, SQL, PySpark logic and pipeline implementations and be capable of identifying technical weaknesses or better approaches.Lead and guide Data Engineers through implementation — not simply track their tasks.Establish reconciliation and data-quality controls proving that required source data has been successfully ingested, processed and retained.Lead technical investigation and resolution of complex data and pipeline issues.Coordinate data sourcing and migrations across multiple systems and engineering teams.Ensure the solution is scalable, supportable, auditable and appropriate for a regulated workplace.Own technical delivery plans, dependencies, risks and blockers.Participate strongly in testing and validation to ensure required data and documents are retained and retrievable.Communicate architecture, technical decisions, risks and delivery status clearly to senior stakeholders.

Required Technical ExperienceStrong hands-on experience is essential.Candidates should have significant practical experience with:DatabricksPySpark / Apache SparkAdvanced SQLApache AirflowAWS, particularly S3 and data services such as AthenaData lake / lakehouse architecturesLarge-scale ETL / ELT pipelinesData modelling and schema designData ingestion and transformationData quality, reconciliation and validationMetadata management and data lineageBatch processing and orchestrationGit and CI/CD practicesExperience with Delta Lake and/or Snowflake is highly desirable.





Architecture ExperienceYou must be able to demonstrate that you have personally designed or materially contributed to architectures involving:Source Systems →

- Ingestion →
- Orchestration →
- Data Processing →
- Data Lake/Lakehouse →
- Retention/Archive →
- Retrieval/APIYou should be able to explain the architectural choices you made, alternatives considered, performance/scalability considerations and how the solution was operationalized.

LeadershipWe are looking for someone who can provide technical leadership to an engineering team.You should be comfortable challenging engineers constructively, reviewing proposed solutions, identifying design or implementation problems and driving the team toward the right technical outcome.You will need sufficient technical depth that senior Data Engineers view you as a credible engineering and architecture leader — not simply the person managing the project plan.

Additional Requirements10+ years of relevant technology/data experience.Strong track record designing and delivering enterprise data platforms.Experience leading Data Engineering teams.Strong technical problem-solving skills and willingness to go deep when required.Experience in banking, financial services or another highly regulated environment strongly preferred.Excellent planning and delivery discipline.Strong written and verbal communication.Comfortable communicating technical concepts to both engineers and senior business stakeholders.Agile/Scrum delivery experience.Experience with JIRA and Confluence.Ability to work independently and take ownership of outcomes.Willingness to cover approximately 4 hours of US working hours (approximately 6:00–10:30pm IST).

What We Are NOT Looking ForThis role is not suitable for a pure Project Manager, Scrum Master or Business Analyst who has managed Data Engineering teams without being technically hands-on.We specifically want candidates who have built and architected data solutions themselves and subsequently moved into technical leadership, while retaining the ability to work directly with the technology.If you are a strong Data Architect / Data Engineering Lead who enjoys remaining close to the technology while owning delivery, we would like to hear from you.

📌 Lead Information Technology Project Manager (Bengaluru)
🏢 Imagineers Group
📍 Bengaluru